Safety and alignment in an era of long-horizon models
Research on safety practices for long-running AI systems.
Overview
OpenAI shares findings from deploying extended-horizon AI models, documenting safety challenges, failure modes, and mitigation strategies. Intended for AI researchers and organizations building long-running systems. Focuses on practical lessons rather than theoretical frameworks.
Pros
- Documents real-world safety failures observed in deployed systems
- Provides practical mitigation strategies from operational experience
- Addresses underexplored risks in long-horizon model deployment
- Freely accessible research for the AI safety community
✕ Cons
- Limited to OpenAI's specific deployment context and scale
- No interactive tools or APIs for direct implementation
- Research findings may not generalize to other architectures
Key Features
Use Cases
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Frequently Asked Questions
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